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An implementation of Bayesian online changepoint detection (Adams and MacKay (2007) <doi:10.48550/arXiv.0710.3742>) with an option for probability based outlier detection and removal (Wendelberger et. al. (2021) <doi:10.48550/arXiv.2112.12899>). Building on the independent multivariate constant mean model implemented in the 'R' package 'ocp', this package models multivariate data as multivariate normal about a linear trend, defined by user input covariates, with an unstructured error covariance. Changepoints are identified based on a probability threshold for windows of points.
| Version: | 1.2 |
| Depends: | R (≥ 3.5.0), methods |
| Imports: | Rcpp (≥ 1.0.7), RcppArmadillo |
| LinkingTo: | Rcpp, RcppArmadillo, RcppDist |
| Suggests: | mvtnorm |
| Published: | 2023-12-13 |
| Author: | Laura Wendelberger [aut], Josh Gray [aut], Brian Reich [aut], Alyson Wilson [aut], Shannon T. Holloway [aut, cre] |
| Maintainer: | Shannon T. Holloway <shannon.t.holloway at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | roboBayes results |
| Reference manual: | roboBayes.pdf |
| Package source: | roboBayes_1.2.tar.gz |
| Windows binaries: | r-devel: roboBayes_1.2.zip, r-release: roboBayes_1.2.zip, r-oldrel: roboBayes_1.2.zip |
| macOS binaries: | r-release (arm64): roboBayes_1.2.tgz, r-oldrel (arm64): roboBayes_1.2.tgz, r-release (x86_64): roboBayes_1.2.tgz, r-oldrel (x86_64): roboBayes_1.2.tgz |
| Old sources: | roboBayes archive |
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